There are two major types of regression analysissimple and multiple regression analysis. Both types consist of dependent and independent variables. Simple linear regression has two variablesdependent and independent. Multiple regression consists of dependent variable and two or more independent variables.

1. Compare and contrast the following processes: forward selection, backward elimination, and stepwise selection.

\fRegression 3, N-24 Regression Analysis: Concession1000 versus .. ndee100, Time, Trend2 Model Summary 5 R-sq R-sqladj) R-sq(pred) 16.7914 92.23% 91.07% 88.67%% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 180.0 15.1 11.92 0.000 Attendee100 -0.260 0.441 -0.59 0.562 1.03 Time 0.43 2.09 0.21 0.838 17.77 Trend2 0.2804 0.0809 3.47 0.002 17.68 Durbin-Watson Statistic Durbin-Watson Statistic = 1.83488 The manager's autocorrelation analysis included the following three regressions. Using Regression 3, do a test of positive first order autocorrelation. Choose whether the following are true or false. In general, the problem with autocorrelation is that time series data are correlated overtime, thus one knows a lot about Yt, by knowing the value of last periods Y...Yt-1. True 0 Fake search e e 9